Future Trends and Roadmap for Quantum-AI in Sustainable Supply Chains

Abstract

Quantum computing and artificial intelligence (AI) will undoubtedly change the concept of supply chain management (SCM), particularly in a world where environmental sustainability, efficiency, and resilience are becoming more and more important to global industries. Massive optimisation, managing uncertainty, and the impact of the environment on logistics and production mitigation are the problems that have overshadowed traditional supply chains. Unsolvable combinatorial problems that classical systems could not possibly solve will be resolved by the advantages of quantum computing and its unmatched computing power. This study combines predictive analytics, case studies of top corporations, and a thorough review of the body of existing literature to approximate the impact of Quantum-AI on Supply Chain Management (SCM). By combining AI with predictive analytics, decision-making, and pattern recognition, Quantum AI systems have the potential to support not only comprehensive visibility and responsive real-time logistics, but also efficient resource allocation. Three areas need to be investigated: improving supply chain resilience, optimising dynamic routes, and information flow to aid in decision-making. According to some research, quantum computing is superior to other methods for scenario analysis and operational reorganisation, particularly in the areas of real-time route optimisation, package optimisation, and disruption management. To exemplify this, the major organizations such as DHL and FedEx have already adopted quantum-enhanced systems to realize a remarkable rise in the efficiency of logistics and resource allocation. The process of developing adoption of Quantum AI to supply chains is outlined in a structured development plan in three phases, including preliminary research and proof-of-concept (2025-2030), pilot projects in big industries (2030-2035) and widespread adoption (post 2035), which can alter the world of global trade and sustainability standards. The earliest applications will be optimization of carbon footprints, automation of smart contracts, and modeling of circular economies. However, despite the potential there are a few challenges. Data incompatibility, cybersecurity, high implementation costs for quantum infrastructure, and the nascent nature of quantum hardware technologies have been identified as the main obstacles. Furthermore, because cross-functional skills are still lacking in supply chain management, artificial intelligence, and quantum knowledge, maximisation is still not possible. This study highlights the importance of taking into account the socioeconomic and ethical implications of quantum artificial intelligence in addition to its technical issues. Achieving sustainable results will require equitable access, technological imbalance, and environmentally friendly practices. Finally, the current research expands our knowledge of how Quantum AI can revolutionise supply chain operations and contribute to the creation of a more intelligent, resilient, and sustainable global economy. The findings have offered tenable suggestions to decision-makers, technology developers, and business executives who want to create a supply chain ecosystem that is prepared for the future.

Received: 17 March 2026  │  Accepted: 12 July 2026  │  Published: 23 July 2026